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Hoteling's T2 control charts are widely used in industries to monitor multivariate processes. The classical estimators, sample mean, and the sample covariance used in T2 control charts are highly sensitive to the outliers in the data. In Phase-I monitoring, control limitsare arrived at using historical data after identifying and removing the multivariate outliers. We propose Hoteling's T2 control charts with high-breakdown robust estimators based onthe reweighted minimum covariance determinant (RMCD) and the reweighted minimumvolume ellipsoid (RMVE) to monitor multivariate observations in Phase-I data. We assessed the performance of these robust control charts based on a large number of MonteCarlo simulations by considering different data scenarios and found that the proposed control charts have better performance compared to existing methods

Robust Control Charts for Monitoring Process Mean of Phase-I Multivariate Individual Observations